Exercise M1.03

Module 1. The Predictive Modeling Pipeline Fitting a scikit-learn model on numerical data
#1

It seems to me that Exercise M1.03 is not complete…

#2

Can you add a few words why you think it is not complete and maybe share a screenshot?

In general: exercises are meant to be done by the learner (hence the “Write your code here” and there is a solution at the bottom). Maybe this is explained somewhere in the intro section of the MOOC but not 100% sure …

#3

To be more explicit if your exercise looks something like this, this is normal:

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Also you can click on “Look at the solution” if you want, although you should probably do so once you have tried to solve the exercise :wink::

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#4

In the other exercises we received much more guidance. That’s why I was wondering whether a piece was missing. But it is fine with me as it is. Thanks

#5

In the other exercises we received much more guidance.

I would say that the previous exercises were added recently (the one in data exploration and the one with setting n_neighbors in KNearestNeighbors) and meant to be very straighforward or beginner-friendly whereas this is the first one that is a bit less so.

But it is fine with me as it is.

OK great! I would say let’s considered it good enough unless somebody else complains :wink:

Of course if you have some improvements suggestions on how to add or improve the guidance, this would be more than welcome!

#6